1$\tau$ MediumMass SR eff.

2$\tau$ Compressed SR eff.

2$\tau$ Compressed SR eff.

2$\tau$ HighMass SR eff.

2$\tau$ HighMass SR eff.

2$\tau$ multibin SR eff.

2$\tau$ multibin SR eff.

2$\tau$ GMSB SR eff.

2$\tau$ GMSB SR eff.

1$\tau$ Compressed SR eff.

1$\tau$ Compressed SR eff.

1$\tau$ MediumMass SR eff.

1$\tau$ MediumMass SR eff.

2$\tau$ Compressed SR eff.

2$\tau$ Compressed SR eff.

2$\tau$ HighMass SR eff.

2$\tau$ HighMass SR eff.

2$\tau$ multibin SR eff.

2$\tau$ multibin SR eff.

2$\tau$ GMSB SR eff.

2$\tau$ GMSB SR eff.

1$\tau$ Compressed SR acceptance.

1$\tau$ Compressed SR acceptance.

1$\tau$ MediumMass SR acceptance.

1$\tau$ MediumMass SR acceptance.

2$\tau$ Compressed SR acceptance.

2$\tau$ Compressed SR acceptance.

2$\tau$ HighMass SR acceptance.

2$\tau$ HighMass SR acceptance.

2$\tau$ multibin SR acceptance.

2$\tau$ multibin SR acceptance.

2$\tau$ GMSB SR acceptance.

2$\tau$ GMSB SR acceptance.

1$\tau$ Compressed SR acceptance.

1$\tau$ Compressed SR acceptance.

1$\tau$ MediumMass SR acceptance.

1$\tau$ MediumMass SR acceptance.

2$\tau$ Compressed SR acceptance.

2$\tau$ Compressed SR acceptance.

2$\tau$ HighMass SR acceptance.

2$\tau$ HighMass SR acceptance.

2$\tau$ multibin SR acceptance.

2$\tau$ multibin SR acceptance.

2$\tau$ GMSB SR acceptance.

2$\tau$ GMSB SR acceptance.

Cutflow table of the $1\tau$ compressed SR for the four signal benchmark scenarios of low, medium, and high mass-splitting in the simplified model as well as the GMSB model.

Cutflow table of the $1\tau$ compressed SR for the four signal benchmark scenarios of low, medium, and high mass-splitting in the simplified model as well as the GMSB model.

Cutflow table of the $1\tau$ medium-mass SR for the four signal benchmark scenarios of low, medium, and high mass-splitting in the simplified model as well as the GMSB model.

Cutflow table of the $1\tau$ medium-mass SR for the four signal benchmark scenarios of low, medium, and high mass-splitting in the simplified model as well as the GMSB model.

Cutflow table of the $2\tau$ compressed SR for the four signal benchmark scenarios of low, medium, and high mass-splitting in the simplified model as well as the GMSB model.

Cutflow table of the $2\tau$ compressed SR for the four signal benchmark scenarios of low, medium, and high mass-splitting in the simplified model as well as the GMSB model.

Cutflow table of the $2\tau$ high-mass SR for the four signal benchmark scenarios of low, medium, and high mass-splitting in the simplified model as well as the GMSB model.

Cutflow table of the $2\tau$ high-mass SR for the four signal benchmark scenarios of low, medium, and high mass-splitting in the simplified model as well as the GMSB model.

Cutflow table of the $2\tau$ multibin SR for the four signal benchmark scenarios of low, medium, and high mass-splitting in the simplified model as well as the GMSB model.

Cutflow table of the $2\tau$ multibin SR for the four signal benchmark scenarios of low, medium, and high mass-splitting in the simplified model as well as the GMSB model.

Cutflow table of the $2\tau$ GMSB SR for the four signal benchmark scenarios of low, medium, and high mass-splitting in the simplified model as well as the GMSB model.

Cutflow table of the $2\tau$ GMSB SR for the four signal benchmark scenarios of low, medium, and high mass-splitting in the simplified model as well as the GMSB model.

Best performing fit setups entering the final combination as a function of the LSP mass and the gluino mass. 'S' marks the simultaneous fit of the four simplified model single-bin SRs, 'M' denotes the simultaneous fit of the two $1\tau$ SRs and the $2\tau$ multibin SR.

Best performing fit setups entering the final combination as a function of the LSP mass and the gluino mass. 'S' marks the simultaneous fit of the four simplified model single-bin SRs, 'M' denotes the simultaneous fit of the two $1\tau$ SRs and the $2\tau$ multibin SR.

Observed exclusion contour at 95% CL as a function of tanBeta and the SUSY-breaking mass scale Lambda.

Observed exclusion contour at 95% CL as a function of tanBeta and the SUSY-breaking mass scale Lambda.

Expected exclusion contour at 95% CL as a function of tanBeta and the SUSY-breaking mass scale Lambda.

Expected exclusion contour at 95% CL as a function of tanBeta and the SUSY-breaking mass scale Lambda.

Observed exclusion contour at 95% CL as a function of the LSP mass and the gluino mass.

Observed exclusion contour at 95% CL as a function of the LSP mass and the gluino mass.

Expected exclusion contour at 95% CL as a function of the LSP mass and the gluino mass.

Expected exclusion contour at 95% CL as a function of the LSP mass and the gluino mass.

Observed upper limits on the production cross section at 95% CL in pb as a function of tanBeta and SUSY breaking mass scale Lambda.

Observed upper limits on the production cross section at 95% CL in pb as a function of tanBeta and SUSY breaking mass scale Lambda.

Observed upper limits on the production cross section at 95% CL in pb as a function of the LSP mass and the gluino mass.

Observed upper limits on the production cross section at 95% CL in pb as a function of the LSP mass and the gluino mass.

Yields of the expected background from the SM in the bins of the multibin SR of the $2\tau$ channel with all bins being simultaneously used to constrain the background prediction. Expectation is given with the scalings computed in the combined fit applied. Uncertainties are statistial plus systematrics. Only the subsamples contributing the respective region are considered.

Yields of the expected background from the SM in the bins of the multibin SR of the $2\tau$ channel with all bins being simultaneously used to constrain the background prediction. Expectation is given with the scalings computed in the combined fit applied. Uncertainties are statistial plus systematrics. Only the subsamples contributing the respective region are considered.

$m_{\mathrm{T}}^{\tau}$ in the compressed $m_{\mathrm{T}}^{\tau}$ VR of the $1\tau$ channel, illustrating the background modeling after the fit. The last bin includes overflow events.

$m_{\mathrm{T}}^{\tau}$ in the compressed $m_{\mathrm{T}}^{\tau}$ VR of the $1\tau$ channel, illustrating the background modeling after the fit. The last bin includes overflow events.

$E_{\mathrm{T}}^{\mathrm{miss}}$ in the compressed $E_{\mathrm{T}}^{\mathrm{miss}}$ VR of the $1\tau$ channel, illustrating the background modeling after the fit. The last bin includes overflow events.

$E_{\mathrm{T}}^{\mathrm{miss}}$ in the compressed $E_{\mathrm{T}}^{\mathrm{miss}}$ VR of the $1\tau$ channel, illustrating the background modeling after the fit. The last bin includes overflow events.

$m_{\mathrm{T}}^{\tau}$ in the medium-mass $m_{\mathrm{T}}^{\tau}$ VR of the $1\tau$ channel, illustrating the background modeling after the fit. The last bin includes overflow events.

$m_{\mathrm{T}}^{\tau}$ in the medium-mass $m_{\mathrm{T}}^{\tau}$ VR of the $1\tau$ channel, illustrating the background modeling after the fit. The last bin includes overflow events.

$E_{\mathrm{T}}^{\mathrm{miss}}$ in the medium-mass $E_{\mathrm{T}}^{\mathrm{miss}}$ VR of the $1\tau$ channel, illustrating the background modeling after the fit. The last bin includes overflow events.

$E_{\mathrm{T}}^{\mathrm{miss}}$ in the medium-mass $E_{\mathrm{T}}^{\mathrm{miss}}$ VR of the $1\tau$ channel, illustrating the background modeling after the fit. The last bin includes overflow events.

$H_{\mathrm{T}}$ in the medium-mass $H_{\mathrm{T}}$ VR of the $1\tau$ channel, illustrating the background modeling after the fit. The last bin includes overflow events.

$H_{\mathrm{T}}$ in the medium-mass $H_{\mathrm{T}}$ VR of the $1\tau$ channel, illustrating the background modeling after the fit. The last bin includes overflow events.

$m_{\mathrm{T}}^{\tau_1}$ + $m_{\mathrm{T}}^{\tau_2}$ in the top VR of the $2\tau$ channel, illustrating the background modeling after the fit. The last bin includes overflow events.

$m_{\mathrm{T}}^{\tau_1}$ + $m_{\mathrm{T}}^{\tau_2}$ in the top VR of the $2\tau$ channel, illustrating the background modeling after the fit. The last bin includes overflow events.

$H_{\mathrm{T}}$ in the $W$ VR of the $2\tau$ channel, illustrating the background modeling after the fit. The last bin includes overflow events.

$H_{\mathrm{T}}$ in the $W$ VR of the $2\tau$ channel, illustrating the background modeling after the fit. The last bin includes overflow events.

$m_{\mathrm{T}}^{\tau_1}$ + $m_{\mathrm{T}}^{\tau_2}$ in the $Z$ VR of the $2\tau$ channel, illustrating the background modeling after the fit. The last bin includes overflow events.

$m_{\mathrm{T}}^{\tau_1}$ + $m_{\mathrm{T}}^{\tau_2}$ in the $Z$ VR of the $2\tau$ channel, illustrating the background modeling after the fit. The last bin includes overflow events.

$m_{\mathrm{T}}^{\tau}$ in the compressed SR of the $1\tau$ channel before application of the $m_{\mathrm{T}}^{\tau}$ > 80 GeV requirement. The last bin includes overflow events. Signal predictions corresponding to the simplified model scenarios of low (LM), medium (MM), and high mass-splitting (HM) as well as for the GMSB benchmark are given.

$m_{\mathrm{T}}^{\tau}$ in the compressed SR of the $1\tau$ channel before application of the $m_{\mathrm{T}}^{\tau}$ > 80 GeV requirement. The last bin includes overflow events. Signal predictions corresponding to the simplified model scenarios of low (LM), medium (MM), and high mass-splitting (HM) as well as for the GMSB benchmark are given.

$H_{\mathrm{T}}$ in the medium-mass SR of the $1\tau$ channel before application of the $H_{\mathrm{T}}$ > 1000 GeV requirement. The last bin includes overflow events. Signal predictions corresponding to the simplified model scenarios of low (LM), medium (MM), and high mass-splitting (HM) as well as for the GMSB benchmark are given.

$H_{\mathrm{T}}$ in the medium-mass SR of the $1\tau$ channel before application of the $H_{\mathrm{T}}$ > 1000 GeV requirement. The last bin includes overflow events. Signal predictions corresponding to the simplified model scenarios of low (LM), medium (MM), and high mass-splitting (HM) as well as for the GMSB benchmark are given.

$m_{\mathrm{T}}^{\mathrm{sum}}$ in the compressed SR of the $2\tau$ channel before application of the $m_{\mathrm{T}}^{\mathrm{sum}}$ > 1600 GeV requirement. The last bin includes overflow events. Signal predictions corresponding to the simplified model scenarios of low (LM), medium (MM), and high mass-splitting (HM) as well as for the GMSB benchmark are given.

$m_{\mathrm{T}}^{\mathrm{sum}}$ in the compressed SR of the $2\tau$ channel before application of the $m_{\mathrm{T}}^{\mathrm{sum}}$ > 1600 GeV requirement. The last bin includes overflow events. Signal predictions corresponding to the simplified model scenarios of low (LM), medium (MM), and high mass-splitting (HM) as well as for the GMSB benchmark are given.

$H_{\mathrm{T}}$ in the high-mass SR of the $2\tau$ channel before application of the $H_{\mathrm{T}}$ > 1100 GeV requirement. The last bin includes overflow events. Signal predictions corresponding to the simplified model scenarios of low (LM), medium (MM), and high mass-splitting (HM) as well as for the GMSB benchmark are given.

$H_{\mathrm{T}}$ in the high-mass SR of the $2\tau$ channel before application of the $H_{\mathrm{T}}$ > 1100 GeV requirement. The last bin includes overflow events. Signal predictions corresponding to the simplified model scenarios of low (LM), medium (MM), and high mass-splitting (HM) as well as for the GMSB benchmark are given.

mT(tau_1) + mT(tau_2) in the multibin SR of the 2T channel. The last bin includes overflow events. Signal predictions corresponding to the simplified model scenarios of low (LM), medium (MM), and high mass-splitting (HM) as well as for the GMSB benchmark are given.

mT(tau_1) + mT(tau_2) in the multibin SR of the 2T channel. The last bin includes overflow events. Signal predictions corresponding to the simplified model scenarios of low (LM), medium (MM), and high mass-splitting (HM) as well as for the GMSB benchmark are given.

$H_{\mathrm{T}}$ in the GMSB SR of the $2\tau$ channel before application of the $H_{\mathrm{T}}$ > 1900 GeV requirement. The last bin includes overflow events. Signal predictions corresponding to the simplified model scenarios of low (LM), medium (MM), and high mass-splitting (HM) as well as for the GMSB benchmark are given.

$H_{\mathrm{T}}$ in the GMSB SR of the $2\tau$ channel before application of the $H_{\mathrm{T}}$ > 1900 GeV requirement. The last bin includes overflow events. Signal predictions corresponding to the simplified model scenarios of low (LM), medium (MM), and high mass-splitting (HM) as well as for the GMSB benchmark are given.

Exclusion limits on higgsino pair production divided by the theory cross-section.The results of the low-mass analysis are used below m(higgsino) = 300 GeV, while those of the high-mass analysis are used above. The figure shows the observed and expected 95% upper limits on the higgsino pair production cross-section as a function of m(higgsino).

Observed and expected 95% limits in the m(higgsino) vs BR(higgsino to higgs+gravitino) plane. The regions above the lines are excluded by the analyses.

The observed and expected 95% upper limits on the total pair production cross section for degenerate higgsinos as a function of m(higgsino) for the high-mass search. Only the high-mass analysis results are used in this figure.

The observed and expected 95% upper limits on the total pair production cross section for degenerate higgsinos as a function of m(higgsino) for the high-mass search, divided by the theory cross section. Only the high-mass analysis results are used in this figure.

The observed and expected 95% upper limits on the total pair production cross section for degenerate higgsinos as a function of m(higgsino) for the low-mass search. Only the low-mass analysis results are used in this figure.

The observed and expected 95% upper limits on the total pair production cross section for degenerate higgsinos as a function of m(higgsino) for the low-mass search, divided by the theory cross section. Only the low-mass analysis results are used in this figure.

Particle-level acceptance for the low-mass discovery signal regions low-SR-MET0-meff440 and low-SR-MET150-meff440, shown as a function of higgsino mass. The acceptance is defined as the fraction of signal events passing the particle-level event selection that emulates the detector-level selection. The acceptance calculation considers only those signal events where both higgsinos decay to Higgs bosons that subsequently both decay to b-quarks.

The experimental efficiency of the low-mass analysis, for the two discovery signal regions low-SR-MET0-meff440 and low-SR-MET150-meff440, as a function of higgsino mass. The experimental efficiency is defined as the number of events passing the detector-level event selection divided by the number of events passing the event selection for a perfect detector. The denominator is obtained by implementing particle-level event selection that emulate the detector-level selection. Such particle-level selection is not applied on the numerator.

Particle-level acceptance for the high-mass discovery signal regions SR-4b-meff1-A-disc and SR-3b-meff3-A, shown as a function of higgsino mass. The acceptance is defined as the fraction of signal events passing the particle-level event selection that emulates the detector-level selection. The acceptance calculation considers only those signal events where both higgsinos decay to Higgs bosons that subsequently both decay to b-quarks.

The experimental efficiency of the high-mass analysis, for the two discovery signal regions SR-4b-meff1-A-disc and SR-3b-meff3-A, as a function of higgsino mass. The experimental efficiency is defined as the number of events passing the detector-level event selection divided by the number of events passing the event selection for a perfect detector. The denominator is obtained by implementing particle-level event selection that emulate the detector-level selection. Such particle-level selection is not applied on the numerator.

Example cutflow for SR-3b-meff3-A.

Example cutflow for SR-4b-meff1-A-disc.

Cutflow for low-mass analysis for each signal mass point.

Dijet mass spectra after the background only fit with the background prediction in the high-mass region with two b-tags.

Dijet mass spectra after the background only fit with the background prediction in the low-mass region with two b-tags.

The online b-tagging efficiency with respect to the offline b-tagging efficiency as a function of pT. The b-tagging online and offline working points correspond to an efficiency of 60% and 70%, respectively.

Observed and expected 95% credibility-level upper limits on the cross-section for the b* model in the high-mass region with inclusive b-jet selection.

Observed and expected 95% credibility-level upper limits on the cross-section times branching ratio for the SSM and leptophobic Z' models in the low- and high-mass region with two b-tags selection.

Observed and expected 95% credibility-level upper limits on the cross-section for DM Z' models in the low-mass region with two b-tags selection. The Z' is expected to decay to all five quark flavors other than the top quark and the mediator to SM quark coupling (gSM) equal to 0.1 is assumed.

Observed and expected 95% credibility-level upper limits on the cross-section times branching ratio for DM Z'->bb models in the high-mass region with two b-tags selection. The Z' is expected to decay to bb only and the mediator to SM quark coupling (gSM) equal to 0.25 is assumed.

Observed and expected 95% credibility-level upper limits on cross section times acceptance times branching ratio of X --> bb, including kinematic acceptance and b-tagging efficiencies, for resonances with intrinsic width smaller than the detector resolution. The width of the Gaussian reconstructed shape is dominated by the dijet mass resolution. The table shows the limits obtained from the high-mass inclusive one b-tag selection.

Observed and expected 95% credibility-level upper limits on cross section times acceptance times branching ratio of X --> bb, including kinematic acceptance and b-tagging efficiencies, for resonances with intrinsic width smaller than the detector resolution. The width of the Gaussian reconstructed shape is dominated by the dijet mass resolution. The table shows the limits obtained from the combined low- and high-mass two b-tags selection.

The mass distributions for the inclusive one b-tagged selection and two b-tagged selection using an integrated luminosity of 36.1 $fb^{-1}$. The inclusive one b-tagged Pythia8 MC distribution is normalized to the inclusive one b-tagged data. The two b-tagged Pythia8 MC distribution is normalized to the two b-tagged data. The systematic uncertainty band is dominated by the b-tagging scale factor and the b-jet energy scale.

Signal acceptance times efficiency for inclusive 1 b-tag and 2 b-tag categories as a function of the simulated b* and the Z' masses.

Signal acceptance times efficiency for 2 b-tag categories as a function of the simulated Z' masses.

The flavor composition of the simulated dijet background as a function of dijet mass before tagging. The fraction of the six combinations of the b-jet , c-jet and light-flavor jet are shown. All offline selections are applied.

The flavor composition of the simulated dijet background as a function of dijet mass with inclusive one b-tag. The fraction of the six combinations of the b-jet , c-jet and light-flavor jet are shown. All offline selections are applied.

The flavor composition of the simulated dijet background as a function of dijet mass with two b-tags. The fraction of the six combinations of the b-jet , c-jet and light-flavor jet are shown. All offline selections are applied.

Observed and expected 95% credibility-level upper limits on cross section times acceptance times branching ratio of X --> bb, including kinematic acceptance and b-tagging efficiencies, for resonances exhibiting a generic Gaussian shape at particle level. The table shows the limits obtained from the inclusive b-jet selection. The limits corresponding to Gaussian-shaped resonances with width of Γ(X)/m(X) = 3%.

Observed and expected 95% credibility-level upper limits on cross section times acceptance times branching ratio of X --> bb, including kinematic acceptance and b-tagging efficiencies, for resonances exhibiting a generic Gaussian shape at particle level. The table shows the limits obtained from the inclusive b-jet selection. The limits corresponding to Gaussian-shaped resonances with width of Γ(X)/m(X) = 7%.

Observed and expected 95% credibility-level upper limits on cross section times acceptance times branching ratio of X --> bb, including kinematic acceptance and b-tagging efficiencies, for resonances exhibiting a generic Gaussian shape at particle level. The table shows the limits obtained from the inclusive b-jet selection. The limits corresponding to Gaussian-shaped resonances with width of Γ(X)/m(X) = 10%.

Observed and expected 95% credibility-level upper limits on cross section times acceptance times branching ratio of X --> bb, including kinematic acceptance and b-tagging efficiencies, for resonances exhibiting a generic Gaussian shape at particle level. The table shows the limits obtained from the inclusive b-jet selection. The limits corresponding to Gaussian-shaped resonances with width of Γ(X)/m(X) = 15%.

Observed and expected 95% credibility-level upper limits on cross section times acceptance times branching ratio of X --> bb, including kinematic acceptance and b-tagging efficiencies, for resonances exhibiting a generic Gaussian shape at particle level. The table shows the limits obtained from the combined low- and high-mass two b-tags selection. The limits corresponding to Gaussian-shaped resonances with width of Γ(X)/m(X) = 3%.

Observed and expected 95% credibility-level upper limits on cross section times acceptance times branching ratio of X --> bb, including kinematic acceptance and b-tagging efficiencies, for resonances exhibiting a generic Gaussian shape at particle level. The table shows the limits obtained from the combined low- and high-mass two b-tags selection. The limits corresponding to Gaussian-shaped resonances with width of Γ(X)/m(X) = 7%.

Observed and expected 95% credibility-level upper limits on cross section times acceptance times branching ratio of X --> bb, including kinematic acceptance and b-tagging efficiencies, for resonances exhibiting a generic Gaussian shape at particle level. The table shows the limits obtained from the combined low- and high-mass two b-tags selection. The limits corresponding to Gaussian-shaped resonances with width of Γ(X)/m(X) = 10%.

Observed and expected 95% credibility-level upper limits on cross section times acceptance times branching ratio of X --> bb, including kinematic acceptance and b-tagging efficiencies, for resonances exhibiting a generic Gaussian shape at particle level. The table shows the limits obtained from the combined low- and high-mass two b-tags selection. The limits corresponding to Gaussian-shaped resonances with width of Γ(X)/m(X) = 15%.

Acceptance for SR1 in the $\tilde{t}_1/\tilde{c}_1-\tilde{\chi}_1^0$ mass plane.

Acceptance for SR2 in the $\tilde{t}_1/\tilde{c}_1-\tilde{\chi}_1^0$ mass plane.

Acceptance for SR2 in the $\tilde{t}_1/\tilde{c}_1-\tilde{\chi}_1^0$ mass plane.

Acceptance for SR2 in the $\tilde{t}_1/\tilde{c}_1-\tilde{\chi}_1^0$ mass plane.

Acceptance for SR3 in the $\tilde{t}_1/\tilde{c}_1-\tilde{\chi}_1^0$ mass plane.

Acceptance for SR3 in the $\tilde{t}_1/\tilde{c}_1-\tilde{\chi}_1^0$ mass plane.

Acceptance for SR3 in the $\tilde{t}_1/\tilde{c}_1-\tilde{\chi}_1^0$ mass plane.

Acceptance for SR4 in the $\tilde{t}_1/\tilde{c}_1-\tilde{\chi}_1^0$ mass plane.

Acceptance for SR4 in the $\tilde{t}_1/\tilde{c}_1-\tilde{\chi}_1^0$ mass plane.

Acceptance for SR4 in the $\tilde{t}_1/\tilde{c}_1-\tilde{\chi}_1^0$ mass plane.

Acceptance for SR5 in the $\tilde{t}_1/\tilde{c}_1-\tilde{\chi}_1^0$ mass plane.

Acceptance for SR5 in the $\tilde{t}_1/\tilde{c}_1-\tilde{\chi}_1^0$ mass plane.

Acceptance for SR5 in the $\tilde{t}_1/\tilde{c}_1-\tilde{\chi}_1^0$ mass plane.

Acceptance for best expected CLS SR in the $\tilde{t}_1/\tilde{c}_1-\tilde{\chi}_1^0$ mass plane.

Acceptance for best expected CLS SR in the $\tilde{t}_1/\tilde{c}_1-\tilde{\chi}_1^0$ mass plane.

Detector efficiency for best expected CLS SR in the $\tilde{t}_1/\tilde{c}_1-\tilde{\chi}_1^0$ mass plane.

Detector efficiency for SR1 in the $\tilde{t}_1/\tilde{c}_1-\tilde{\chi}_1^0$ mass plane.

Detector efficiency for SR1 in the $\tilde{t}_1/\tilde{c}_1-\tilde{\chi}_1^0$ mass plane.

Detector efficiency for SR1 in the $\tilde{t}_1/\tilde{c}_1-\tilde{\chi}_1^0$ mass plane.

Detector efficiency for SR2 in the $\tilde{t}_1/\tilde{c}_1-\tilde{\chi}_1^0$ mass plane.

Detector efficiency for SR2 in the $\tilde{t}_1/\tilde{c}_1-\tilde{\chi}_1^0$ mass plane.

Detector efficiency for SR2 in the $\tilde{t}_1/\tilde{c}_1-\tilde{\chi}_1^0$ mass plane.

Detector efficiency for SR3 in the $\tilde{t}_1/\tilde{c}_1-\tilde{\chi}_1^0$ mass plane.

Detector efficiency for SR3 in the $\tilde{t}_1/\tilde{c}_1-\tilde{\chi}_1^0$ mass plane.

Detector efficiency for SR3 in the $\tilde{t}_1/\tilde{c}_1-\tilde{\chi}_1^0$ mass plane.

Detector efficiency for SR4 in the $\tilde{t}_1/\tilde{c}_1-\tilde{\chi}_1^0$ mass plane.

Detector efficiency for SR4 in the $\tilde{t}_1/\tilde{c}_1-\tilde{\chi}_1^0$ mass plane.

Detector efficiency for SR4 in the $\tilde{t}_1/\tilde{c}_1-\tilde{\chi}_1^0$ mass plane.

Detector efficiency for SR5 in the $\tilde{t}_1/\tilde{c}_1-\tilde{\chi}_1^0$ mass plane.

Detector efficiency for SR5 in the $\tilde{t}_1/\tilde{c}_1-\tilde{\chi}_1^0$ mass plane.

Detector efficiency for SR5 in the $\tilde{t}_1/\tilde{c}_1-\tilde{\chi}_1^0$ mass plane.

Detector efficiency for best expected CLS SR in the $\tilde{t}_1/\tilde{c}_1-\tilde{\chi}_1^0$ mass plane.

Detector efficiency for best expected CLS SR in the $\tilde{t}_1/\tilde{c}_1-\tilde{\chi}_1^0$ mass plane.

Expected exclusion limit at 95% CL in the $m(\tilde t_1/\tilde c_1)$-$m(\tilde\chi^0_1)$ plane for the stop/scharm pair production scenario.

Expected exclusion limit at 95% CL in the $m(\tilde t_1/\tilde c_1)$-$m(\tilde\chi^0_1)$ plane for the stop/scharm pair production scenario.

Expected exclusion limit at 95% CL in the $m(\tilde t_1/\tilde c_1)$-$m(\tilde\chi^0_1)$ plane for the stop/scharm pair production scenario.

Observed exclusion limit at 95% CL in the $m(\tilde t_1/\tilde c_1)$-$m(\tilde\chi^0_1)$ plane for the stop/scharm pair production scenario.

Observed exclusion limit at 95% CL in the $m(\tilde t_1/\tilde c_1)$-$m(\tilde\chi^0_1)$ plane for the stop/scharm pair production scenario.

Observed exclusion limit at 95% CL in the $m(\tilde t_1/\tilde c_1)$-$m(\tilde\chi^0_1)$ plane for the stop/scharm pair production scenario.

SR1 expected exclusion limit at 95% CL in the $m(\tilde t_1/\tilde c_1)$-$m(\tilde\chi^0_1)$ plane for the stop/scharm pair production scenario.

SR1 expected exclusion limit at 95% CL in the $m(\tilde t_1/\tilde c_1)$-$m(\tilde\chi^0_1)$ plane for the stop/scharm pair production scenario.

SR1 expected exclusion limit at 95% CL in the $m(\tilde t_1/\tilde c_1)$-$m(\tilde\chi^0_1)$ plane for the stop/scharm pair production scenario.

SR1 observed exclusion limit at 95% CL in the $m(\tilde t_1/\tilde c_1)$-$m(\tilde\chi^0_1)$ plane for the stop/scharm pair production scenario.

SR1 observed exclusion limit at 95% CL in the $m(\tilde t_1/\tilde c_1)$-$m(\tilde\chi^0_1)$ plane for the stop/scharm pair production scenario.

SR1 observed exclusion limit at 95% CL in the $m(\tilde t_1/\tilde c_1)$-$m(\tilde\chi^0_1)$ plane for the stop/scharm pair production scenario.

SR2 expected exclusion limit at 95% CL in the $m(\tilde t_1/\tilde c_1)$-$m(\tilde\chi^0_1)$ plane for the stop/scharm pair production scenario.

SR2 expected exclusion limit at 95% CL in the $m(\tilde t_1/\tilde c_1)$-$m(\tilde\chi^0_1)$ plane for the stop/scharm pair production scenario.

SR2 expected exclusion limit at 95% CL in the $m(\tilde t_1/\tilde c_1)$-$m(\tilde\chi^0_1)$ plane for the stop/scharm pair production scenario.

SR2 observed exclusion limit at 95% CL in the $m(\tilde t_1/\tilde c_1)$-$m(\tilde\chi^0_1)$ plane for the stop/scharm pair production scenario.

SR2 observed exclusion limit at 95% CL in the $m(\tilde t_1/\tilde c_1)$-$m(\tilde\chi^0_1)$ plane for the stop/scharm pair production scenario.

SR2 observed exclusion limit at 95% CL in the $m(\tilde t_1/\tilde c_1)$-$m(\tilde\chi^0_1)$ plane for the stop/scharm pair production scenario.

SR3 expected exclusion limit at 95% CL in the $m(\tilde t_1/\tilde c_1)$-$m(\tilde\chi^0_1)$ plane for the stop/scharm pair production scenario.

SR3 expected exclusion limit at 95% CL in the $m(\tilde t_1/\tilde c_1)$-$m(\tilde\chi^0_1)$ plane for the stop/scharm pair production scenario.

SR3 expected exclusion limit at 95% CL in the $m(\tilde t_1/\tilde c_1)$-$m(\tilde\chi^0_1)$ plane for the stop/scharm pair production scenario.

SR3 observed exclusion limit at 95% CL in the $m(\tilde t_1/\tilde c_1)$-$m(\tilde\chi^0_1)$ plane for the stop/scharm pair production scenario.

SR3 observed exclusion limit at 95% CL in the $m(\tilde t_1/\tilde c_1)$-$m(\tilde\chi^0_1)$ plane for the stop/scharm pair production scenario.

SR3 observed exclusion limit at 95% CL in the $m(\tilde t_1/\tilde c_1)$-$m(\tilde\chi^0_1)$ plane for the stop/scharm pair production scenario.

SR4 expected exclusion limit at 95% CL in the $m(\tilde t_1/\tilde c_1)$-$m(\tilde\chi^0_1)$ plane for the stop/scharm pair production scenario.

SR4 expected exclusion limit at 95% CL in the $m(\tilde t_1/\tilde c_1)$-$m(\tilde\chi^0_1)$ plane for the stop/scharm pair production scenario.

SR4 expected exclusion limit at 95% CL in the $m(\tilde t_1/\tilde c_1)$-$m(\tilde\chi^0_1)$ plane for the stop/scharm pair production scenario.

SR4 observed exclusion limit at 95% CL in the $m(\tilde t_1/\tilde c_1)$-$m(\tilde\chi^0_1)$ plane for the stop/scharm pair production scenario.

SR4 observed exclusion limit at 95% CL in the $m(\tilde t_1/\tilde c_1)$-$m(\tilde\chi^0_1)$ plane for the stop/scharm pair production scenario.

SR4 observed exclusion limit at 95% CL in the $m(\tilde t_1/\tilde c_1)$-$m(\tilde\chi^0_1)$ plane for the stop/scharm pair production scenario.

SR5 expected exclusion limit at 95% CL in the $m(\tilde t_1/\tilde c_1)$-$m(\tilde\chi^0_1)$ plane for the stop/scharm pair production scenario.

SR5 expected exclusion limit at 95% CL in the $m(\tilde t_1/\tilde c_1)$-$m(\tilde\chi^0_1)$ plane for the stop/scharm pair production scenario.

SR5 expected exclusion limit at 95% CL in the $m(\tilde t_1/\tilde c_1)$-$m(\tilde\chi^0_1)$ plane for the stop/scharm pair production scenario.

SR5 observed exclusion limit at 95% CL in the $m(\tilde t_1/\tilde c_1)$-$m(\tilde\chi^0_1)$ plane for the stop/scharm pair production scenario.

SR5 observed exclusion limit at 95% CL in the $m(\tilde t_1/\tilde c_1)$-$m(\tilde\chi^0_1)$ plane for the stop/scharm pair production scenario.

SR5 observed exclusion limit at 95% CL in the $m(\tilde t_1/\tilde c_1)$-$m(\tilde\chi^0_1)$ plane for the stop/scharm pair production scenario.

Upper limits on signal cross sections and exclusion limits at 95% CL for the best expected SR in the $m(\tilde t_1/\tilde c_1)$-$m(\tilde\chi^0_1)$ plane for the stop/scharm pair production scenario.

Upper limits on signal cross sections and exclusion limits at 95% CL for SR1 in the $m(\tilde t_1/\tilde c_1)$-$m(\tilde\chi^0_1)$ plane for the stop/scharm pair production scenario.

Upper limits on signal cross sections and exclusion limits at 95% CL for SR1 in the $m(\tilde t_1/\tilde c_1)$-$m(\tilde\chi^0_1)$ plane for the stop/scharm pair production scenario.

Upper limits on signal cross sections and exclusion limits at 95% CL for SR1 in the $m(\tilde t_1/\tilde c_1)$-$m(\tilde\chi^0_1)$ plane for the stop/scharm pair production scenario.

Upper limits on signal cross sections and exclusion limits at 95% CL for SR2 in the $m(\tilde t_1/\tilde c_1)$-$m(\tilde\chi^0_1)$ plane for the stop/scharm pair production scenario.

Upper limits on signal cross sections and exclusion limits at 95% CL for SR2 in the $m(\tilde t_1/\tilde c_1)$-$m(\tilde\chi^0_1)$ plane for the stop/scharm pair production scenario.

Upper limits on signal cross sections and exclusion limits at 95% CL for SR2 in the $m(\tilde t_1/\tilde c_1)$-$m(\tilde\chi^0_1)$ plane for the stop/scharm pair production scenario.

Upper limits on signal cross sections and exclusion limits at 95% CL for SR3 in the $m(\tilde t_1/\tilde c_1)$-$m(\tilde\chi^0_1)$ plane for the stop/scharm pair production scenario.

Upper limits on signal cross sections and exclusion limits at 95% CL for SR3 in the $m(\tilde t_1/\tilde c_1)$-$m(\tilde\chi^0_1)$ plane for the stop/scharm pair production scenario.

Upper limits on signal cross sections and exclusion limits at 95% CL for SR3 in the $m(\tilde t_1/\tilde c_1)$-$m(\tilde\chi^0_1)$ plane for the stop/scharm pair production scenario.

Upper limits on signal cross sections and exclusion limits at 95% CL for SR4 in the $m(\tilde t_1/\tilde c_1)$-$m(\tilde\chi^0_1)$ plane for the stop/scharm pair production scenario.

Upper limits on signal cross sections and exclusion limits at 95% CL for SR4 in the $m(\tilde t_1/\tilde c_1)$-$m(\tilde\chi^0_1)$ plane for the stop/scharm pair production scenario.

Upper limits on signal cross sections and exclusion limits at 95% CL for SR4 in the $m(\tilde t_1/\tilde c_1)$-$m(\tilde\chi^0_1)$ plane for the stop/scharm pair production scenario.

Upper limits on signal cross sections and exclusion limits at 95% CL for SR5 in the $m(\tilde t_1/\tilde c_1)$-$m(\tilde\chi^0_1)$ plane for the stop/scharm pair production scenario.

Upper limits on signal cross sections and exclusion limits at 95% CL for SR5 in the $m(\tilde t_1/\tilde c_1)$-$m(\tilde\chi^0_1)$ plane for the stop/scharm pair production scenario.

Upper limits on signal cross sections and exclusion limits at 95% CL for SR5 in the $m(\tilde t_1/\tilde c_1)$-$m(\tilde\chi^0_1)$ plane for the stop/scharm pair production scenario.

Upper limits on signal cross sections and exclusion limits at 95% CL for the best expected SR in the $m(\tilde t_1/\tilde c_1)$-$m(\tilde\chi^0_1)$ plane for the stop/scharm pair production scenario.

Upper limits on signal cross sections and exclusion limits at 95% CL for the best expected SR in the $m(\tilde t_1/\tilde c_1)$-$m(\tilde\chi^0_1)$ plane for the stop/scharm pair production scenario.

Minimum branching ratio excluded at 95% CL, assuming no sensitivity for other decay possibilities, in the $m(\tilde t_1/\tilde c_1)$-$m(\tilde\chi^0_1)$ plane for the stop/scharm pair production scenario.

Minimum branching ratio excluded at 95% CL, assuming no sensitivity for other decay possibilities, in the $m(\tilde t_1/\tilde c_1)$-$m(\tilde\chi^0_1)$ plane for the stop/scharm pair production scenario.

Minimum branching ratio excluded at 95% CL, assuming no sensitivity for other decay possibilities, in the $m(\tilde t_1/\tilde c_1)$-$m(\tilde\chi^0_1)$ plane for the stop/scharm pair production scenario.

The signal region with the best expected CLS value for each signal in the $\tilde{t}_1/\tilde{c}_1-\tilde{\chi}_1^0$ mass plane.

The signal region with the best expected CLS value for each signal in the $\tilde{t}_1/\tilde{c}_1-\tilde{\chi}_1^0$ mass plane.

The signal region with the best expected CLS value for each signal in the $\tilde{t}_1/\tilde{c}_1-\tilde{\chi}_1^0$ mass plane.

Expected exclusion limit at 95% CL in the $m(\tilde t_1/\tilde c_1)$-$\Delta m$ plane for the stop/scharm pair production scenario.

Expected exclusion limit at 95% CL in the $m(\tilde t_1/\tilde c_1)$-$\Delta m$ plane for the stop/scharm pair production scenario.

Expected exclusion limit at 95% CL in the $m(\tilde t_1/\tilde c_1)$-$\Delta m$ plane for the stop/scharm pair production scenario.

Observed exclusion limit at 95% CL in the $m(\tilde t_1/\tilde c_1)$-$\Delta m$ plane for the stop/scharm pair production scenario.

Observed exclusion limit at 95% CL in the $m(\tilde t_1/\tilde c_1)$-$\Delta m$ plane for the stop/scharm pair production scenario.

Observed exclusion limit at 95% CL in the $m(\tilde t_1/\tilde c_1)$-$\Delta m$ plane for the stop/scharm pair production scenario.

Comparison between data and expectation after the background-only fit for the $E_{T}^{miss}$ distribution in SR1. The shaded band indicates detector-related systematic uncertainties and the statistical uncertainties of the MC samples, while the error bars on the data points indicate the data's statistical uncertainty. The final bin in each histogram includes the overflow. The lower panel shows the ratio of the data to the SM prediction after the background-only fit. The distribution is also shown for a representative signal point.

Comparison between data and expectation after the background-only fit for the $E_{T}^{miss}$ distribution in SR1. The shaded band indicates detector-related systematic uncertainties and the statistical uncertainties of the MC samples, while the error bars on the data points indicate the data's statistical uncertainty. The final bin in each histogram includes the overflow. The lower panel shows the ratio of the data to the SM prediction after the background-only fit. The distribution is also shown for a representative signal point.

Comparison between data and expectation after the background-only fit for the $E_{T}^{miss}$ distribution in SR1. The shaded band indicates detector-related systematic uncertainties and the statistical uncertainties of the MC samples, while the error bars on the data points indicate the data's statistical uncertainty. The final bin in each histogram includes the overflow. The lower panel shows the ratio of the data to the SM prediction after the background-only fit. The distribution is also shown for a representative signal point.

Comparison between data and expectation after the background-only fit for the $E_{T}^{miss}$ distribution in SR2. The shaded band indicates detector-related systematic uncertainties and the statistical uncertainties of the MC samples, while the error bars on the data points indicate the data's statistical uncertainty. The final bin in each histogram includes the overflow. The lower panel shows the ratio of the data to the SM prediction after the background-only fit. The distribution is also shown for a representative signal point.

Comparison between data and expectation after the background-only fit for the $E_{T}^{miss}$ distribution in SR2. The shaded band indicates detector-related systematic uncertainties and the statistical uncertainties of the MC samples, while the error bars on the data points indicate the data's statistical uncertainty. The final bin in each histogram includes the overflow. The lower panel shows the ratio of the data to the SM prediction after the background-only fit. The distribution is also shown for a representative signal point.

Comparison between data and expectation after the background-only fit for the $E_{T}^{miss}$ distribution in SR2. The shaded band indicates detector-related systematic uncertainties and the statistical uncertainties of the MC samples, while the error bars on the data points indicate the data's statistical uncertainty. The final bin in each histogram includes the overflow. The lower panel shows the ratio of the data to the SM prediction after the background-only fit. The distribution is also shown for a representative signal point.

Comparison between data and expectation after the background-only fit for the $E_{T}^{miss}$ distribution in SR3. The shaded band indicates detector-related systematic uncertainties and the statistical uncertainties of the MC samples, while the error bars on the data points indicate the data's statistical uncertainty. The final bin in each histogram includes the overflow. The lower panel shows the ratio of the data to the SM prediction after the background-only fit. The distribution is also shown for a representative signal point.

Comparison between data and expectation after the background-only fit for the $E_{T}^{miss}$ distribution in SR3. The shaded band indicates detector-related systematic uncertainties and the statistical uncertainties of the MC samples, while the error bars on the data points indicate the data's statistical uncertainty. The final bin in each histogram includes the overflow. The lower panel shows the ratio of the data to the SM prediction after the background-only fit. The distribution is also shown for a representative signal point.

Comparison between data and expectation after the background-only fit for the $E_{T}^{miss}$ distribution in SR3. The shaded band indicates detector-related systematic uncertainties and the statistical uncertainties of the MC samples, while the error bars on the data points indicate the data's statistical uncertainty. The final bin in each histogram includes the overflow. The lower panel shows the ratio of the data to the SM prediction after the background-only fit. The distribution is also shown for a representative signal point.

Comparison between data and expectation after the background-only fit for the $E_{T}^{miss}$ distribution in SR4. The shaded band indicates detector-related systematic uncertainties and the statistical uncertainties of the MC samples, while the error bars on the data points indicate the data's statistical uncertainty. The final bin in each histogram includes the overflow. The lower panel shows the ratio of the data to the SM prediction after the background-only fit. The distribution is also shown for a representative signal point.

Comparison between data and expectation after the background-only fit for the $E_{T}^{miss}$ distribution in SR4. The shaded band indicates detector-related systematic uncertainties and the statistical uncertainties of the MC samples, while the error bars on the data points indicate the data's statistical uncertainty. The final bin in each histogram includes the overflow. The lower panel shows the ratio of the data to the SM prediction after the background-only fit. The distribution is also shown for a representative signal point.

Comparison between data and expectation after the background-only fit for the $E_{T}^{miss}$ distribution in SR4. The shaded band indicates detector-related systematic uncertainties and the statistical uncertainties of the MC samples, while the error bars on the data points indicate the data's statistical uncertainty. The final bin in each histogram includes the overflow. The lower panel shows the ratio of the data to the SM prediction after the background-only fit. The distribution is also shown for a representative signal point.

Comparison between data and expectation after the background-only fit for the $E_{T}^{miss}$ distribution in SR5. The shaded band indicates detector-related systematic uncertainties and the statistical uncertainties of the MC samples, while the error bars on the data points indicate the data's statistical uncertainty. The final bin in each histogram includes the overflow. The lower panel shows the ratio of the data to the SM prediction after the background-only fit. The distribution is also shown for a representative signal point.

Comparison between data and expectation after the background-only fit for the $E_{T}^{miss}$ distribution in SR5. The shaded band indicates detector-related systematic uncertainties and the statistical uncertainties of the MC samples, while the error bars on the data points indicate the data's statistical uncertainty. The final bin in each histogram includes the overflow. The lower panel shows the ratio of the data to the SM prediction after the background-only fit. The distribution is also shown for a representative signal point.

Comparison between data and expectation after the background-only fit for the $E_{T}^{miss}$ distribution in SR5. The shaded band indicates detector-related systematic uncertainties and the statistical uncertainties of the MC samples, while the error bars on the data points indicate the data's statistical uncertainty. The final bin in each histogram includes the overflow. The lower panel shows the ratio of the data to the SM prediction after the background-only fit. The distribution is also shown for a representative signal point.

Cutflow for the $(m_{\tilde{t}}, m_{\tilde{\chi}}) = (450,425)$ GeV signal point for signal region SR1.

Cutflow for the $(m_{\tilde{t}}, m_{\tilde{\chi}}) = (450,425)$ GeV signal point for signal region SR1.

Cutflow for the $(m_{\tilde{t}}, m_{\tilde{\chi}}) = (450,425)$ GeV signal point for signal region SR1.

Cutflow for the $(m_{\tilde{t}}, m_{\tilde{\chi}}) = (500,420)$ GeV signal point for signal region SR2.

Cutflow for the $(m_{\tilde{t}}, m_{\tilde{\chi}}) = (500,420)$ GeV signal point for signal region SR2.

Cutflow for the $(m_{\tilde{t}}, m_{\tilde{\chi}}) = (500,420)$ GeV signal point for signal region SR2.

Cutflow for the $(m_{\tilde{t}}, m_{\tilde{\chi}}) = (500,350)$ GeV signal point for signal region SR3.

Cutflow for the $(m_{\tilde{t}}, m_{\tilde{\chi}}) = (500,350)$ GeV signal point for signal region SR3.

Cutflow for the $(m_{\tilde{t}}, m_{\tilde{\chi}}) = (500,350)$ GeV signal point for signal region SR3.

Cutflow for the $(m_{\tilde{t}}, m_{\tilde{\chi}}) = (600,350)$ GeV signal point for signal region SR4.

Cutflow for the $(m_{\tilde{t}}, m_{\tilde{\chi}}) = (600,350)$ GeV signal point for signal region SR4.

Cutflow for the $(m_{\tilde{t}}, m_{\tilde{\chi}}) = (600,350)$ GeV signal point for signal region SR4.

Cutflow for the $(m_{\tilde{t}}, m_{\tilde{\chi}}) = (900,1)$ GeV signal point for signal region SR5.

Cutflow for the $(m_{\tilde{t}}, m_{\tilde{\chi}}) = (900,1)$ GeV signal point for signal region SR5.

Cutflow for the $(m_{\tilde{t}}, m_{\tilde{\chi}}) = (900,1)$ GeV signal point for signal region SR5.

The observed and expected 95% CL upper limits on the production cross section times branching ratio for SM non-resonant Higgs pair production.

Measured differential cross section with associated uncertainties as a function of COS(THETA*). Each systematic uncertainty sources is fully uncorrelated with the other sources and fully correlated across bins, except for the background modelling systematics for which an uncorrelated treatment across bins is more appropriate.

Measured differential cross section with associated uncertainties as a function of DELTAYRAP(2GAMMA). Each systematic uncertainty sources is fully uncorrelated with the other sources and fully correlated across bins, except for the background modelling systematics for which an uncorrelated treatment across bins is more appropriate.

Measured differential cross section with associated uncertainties as a function of MULT(JET,PT>30 GEV). Each systematic uncertainty sources is fully uncorrelated with the other sources and fully correlated across bins, except for the background modelling systematics for which an uncorrelated treatment across bins is more appropriate.

Measured differential cross section with associated uncertainties as a function of MULT(JET,PT>50 GEV). Each systematic uncertainty sources is fully uncorrelated with the other sources and fully correlated across bins, except for the background modelling systematics for which an uncorrelated treatment across bins is more appropriate.

Measured differential cross section with associated uncertainties as a function of PT(JET1). Each systematic uncertainty sources is fully uncorrelated with the other sources and fully correlated across bins, except for the background modelling systematics for which an uncorrelated treatment across bins is more appropriate.

Measured differential cross section with associated uncertainties as a function of PT(JET2). Each systematic uncertainty sources is fully uncorrelated with the other sources and fully correlated across bins, except for the background modelling systematics for which an uncorrelated treatment across bins is more appropriate.

Measured differential cross section with associated uncertainties as a function of HT. Each systematic uncertainty sources is fully uncorrelated with the other sources and fully correlated across bins, except for the background modelling systematics for which an uncorrelated treatment across bins is more appropriate.

Measured differential cross section with associated uncertainties as a function of YRAP(JET1). Each systematic uncertainty sources is fully uncorrelated with the other sources and fully correlated across bins, except for the background modelling systematics for which an uncorrelated treatment across bins is more appropriate.

Measured differential cross section with associated uncertainties as a function of YRAP(JET2). Each systematic uncertainty sources is fully uncorrelated with the other sources and fully correlated across bins, except for the background modelling systematics for which an uncorrelated treatment across bins is more appropriate.

Measured differential cross section with associated uncertainties as a function of M(2JET). Each systematic uncertainty sources is fully uncorrelated with the other sources and fully correlated across bins, except for the background modelling systematics for which an uncorrelated treatment across bins is more appropriate.

Measured differential cross section with associated uncertainties as a function of DELTAYRAP(2JET). Each systematic uncertainty sources is fully uncorrelated with the other sources and fully correlated across bins, except for the background modelling systematics for which an uncorrelated treatment across bins is more appropriate.

Measured differential cross section with associated uncertainties as a function of ABSDPHI(2JET). Each systematic uncertainty sources is fully uncorrelated with the other sources and fully correlated across bins, except for the background modelling systematics for which an uncorrelated treatment across bins is more appropriate.

Measured differential cross section with associated uncertainties as a function of DPHI(2JET). Each systematic uncertainty sources is fully uncorrelated with the other sources and fully correlated across bins, except for the background modelling systematics for which an uncorrelated treatment across bins is more appropriate.

Measured differential cross section with associated uncertainties as a function of PT(2GAMMA2JET). Each systematic uncertainty sources is fully uncorrelated with the other sources and fully correlated across bins, except for the background modelling systematics for which an uncorrelated treatment across bins is more appropriate.

Measured differential cross section with associated uncertainties as a function of DPHI(2GAMMA,2JET). Each systematic uncertainty sources is fully uncorrelated with the other sources and fully correlated across bins, except for the background modelling systematics for which an uncorrelated treatment across bins is more appropriate.

Measured differential cross section with associated uncertainties as a function of TAUJET. Each systematic uncertainty sources is fully uncorrelated with the other sources and fully correlated across bins, except for the background modelling systematics for which an uncorrelated treatment across bins is more appropriate.

Measured differential cross section with associated uncertainties as a function of SUM(TAUJET). Each systematic uncertainty sources is fully uncorrelated with the other sources and fully correlated across bins, except for the background modelling systematics for which an uncorrelated treatment across bins is more appropriate.

Measured differential cross section with associated uncertainties as a function of PT(2GAMMA) [NJET=0,PT>30 GEV]. Each systematic uncertainty sources is fully uncorrelated with the other sources and fully correlated across bins, except for the background modelling systematics for which an uncorrelated treatment across bins is more appropriate.

Measured differential cross section with associated uncertainties as a function of PT(2GAMMA) [NJET=1,PT>30 GEV]. Each systematic uncertainty sources is fully uncorrelated with the other sources and fully correlated across bins, except for the background modelling systematics for which an uncorrelated treatment across bins is more appropriate.

Measured differential cross section with associated uncertainties as a function of PT(2GAMMA) [NJET=2,PT>30 GEV]. Each systematic uncertainty sources is fully uncorrelated with the other sources and fully correlated across bins, except for the background modelling systematics for which an uncorrelated treatment across bins is more appropriate.

Measured differential cross section with associated uncertainties as a function of PT(2GAMMA) [NJET>=3,PT>30 GEV]. Each systematic uncertainty sources is fully uncorrelated with the other sources and fully correlated across bins, except for the background modelling systematics for which an uncorrelated treatment across bins is more appropriate.

The measured cross sections or cross section limits of the diphoton, VBF-enhanced, Nlepton $\geq$ 1, high $E_{T}^{miss}$, and ttH-enhanced fiducial regions are shown.

Measured differential cross section with associated uncertainties as a function of diphoton transverse momentum in bins of ABS(COS(THETA*)). Each systematic uncertainty sources is fully uncorrelated with the other sources and fully correlated across bins, except for the background modelling systematics for which an uncorrelated treatment across bins is more appropriate.Each systematic uncertainty sources is fully uncorrelated with the other sources.

Non-perturbative correction factors in percent accounting for the impact of hadronisation and the underlying event activity for all measured variables and fiducial regions. Regions of phase space where no reliable estimate could be obtained are listed as 100 without uncertainties. Uncertainties are evaluated by deriving these factors using different generators and tunes as described in the text. No factor are given for the Nlepton $\geq$ 1 and High-$E_{T}^{miss}$ fiducial regions as the gluon fusion contamination in both is negligible.

Isolation efficiencies in percent for gluon fusion $H\rightarrow\gamma\gamma$ for each fiducial region/variable bin measured in this analysis. The isolation efficiency is defined as the probability for both photons to fulfil the isolation criteria (as described in Section 9.1) for events that pass the diphoton kinematic criteria. Regions of phase space where no reliable estimate could be obtained are listed as 100 without uncertainties. Uncertainties are assigned in the same way as for the non-perturbative correction factors: by varying the fragmentation and underlying event modelling. These factors can be multiplied by the kinematic acceptance factors (see Table 29) to extrapolate an inclusive gluon fusion Higgs prediction to the fiducial volume used in this analysis. No factors for the Nlepton $\geq$ 1 and High $E_{T}^{miss}$ fiducial regions are provided as the gluon fusion contamination is negligible.

Combined non-perturbative (Table 27) and particle-level isolation correction factors (Table 28) in percent accounting for the impact of hadronisation and the underlying event activity for all measured variables and fiducial regions. Regions of phase space where no reliable estimate could be obtained are listed as 100 without uncertainties. The uncertainties on the combined values properly take into account the correlations between both multiplicative factors.

Diphoton kinematic acceptances in percent for gluon-gluon fusion for the diphoton fiducial region and all differential variable bins studied in this paper, defined as the probability to fulfill the diphoton kinematic criteria: $p_{T}$/$m_{\gamma\gamma}$ < 0.35 (0.25) for the leading (subleading) photon and $|\eta_{\gamma\gamma}|$ < 2.37. The factors are evaluated using the Powheg NNLOPSevent generator. Uncertainties are taken from PDF variations. QCD scale variations have a negligible impact on these factors. The range of each bin is given in Table 26.

observed statistical correlations between pTyy, Njets, mjj, |DeltaPhijj| and pTj1

ggH default MC + XH predictions

XH ( = VBF + VH + ttH + bbH ) MC predictions

Best-fit values and uncertainties of the production-mode cross sections times branching ratio.

Best-fit values and uncertainties of the simplified template cross sections times branching ratio.

Observed correlations between the measured simplified template cross sections, including both the statistical and systematic uncertainties.

Best-fit values and uncertainties of the simplified template cross sections times branching ratio.

Observed correlations between the measured simplified template cross sections, including both the statistical and systematic uncertainties.

Observed correlations between the measured simplified template cross sections, including both the statistical and systematic uncertainties.

Reconstructed mtb distribution in data and for the background after the fit to the data in the signal region SR2. The statistical uncertainty on data points is calculated using assymetric Poisson confidence intervals.

Reconstructed mtb distribution in data and for the background after the fit to the data in the signal region SR3. The statistical uncertainty on data points is calculated using assymetric Poisson confidence intervals.

Reconstructed mtb distribution in data and for the background after the fit to the data in the validation region VR. The statistical uncertainty on data points is calculated using assymetric Poisson confidence intervals.

Number of expected Standard Model background events including total statistical and systematic uncertainty added in quadrature (calculated before applying the statistical fitting procedure), number of observed events, and the observed and expected 95% CL upper limits on the visible $\tau\nu$ production cross section, $\sigma_{\rm vis} = \sigma(pp \to \tau\nu +X) \cdot \mathcal{A} \cdot \varepsilon$, for $m_{\rm T}$ thresholds ranging from 250 to 1800 GeV. See HepData abstract for details on how to use this data for reinterpretation.

Number of expected Standard Model background events including total statistical and systematic uncertainty added in quadrature (calculated before applying the statistical fitting procedure), number of observed events, and the observed and expected 95% CL upper limits on the visible $\tau\nu$ production cross section, $\sigma_{\rm vis} = \sigma(pp \to \tau\nu +X) \cdot \mathcal{A} \cdot \varepsilon$, for $m_{\rm T}$ thresholds ranging from 250 to 1800 GeV. See HepData abstract for details on how to use this data for reinterpretation.

Number of expected Standard Model background events including total statistical and systematic uncertainty added in quadrature (calculated before applying the statistical fitting procedure), number of observed events, and the observed and expected 95% CL upper limits on the visible $\tau\nu$ production cross section, $\sigma_{\rm vis} = \sigma(pp \to \tau\nu +X) \cdot \mathcal{A} \cdot \varepsilon$, for $m_{\rm T}$ thresholds ranging from 250 to 1800 GeV. See HepData abstract for details on how to use this data for reinterpretation.

Observed and expected 95% CL upper limits on cross section times $\tau\nu$ branching fraction for $W^{\prime}_{\rm SSM}$.

Observed and expected 95% CL upper limits on cross section times $\tau\nu$ branching fraction for $W^{\prime}_{\rm SSM}$.

Observed and expected 95% CL upper limits on cross section times $\tau\nu$ branching fraction for $W^{\prime}_{\rm SSM}$.

Regions of the non-universal G(221) parameter space excluded at 95% CL.

Regions of the non-universal G(221) parameter space excluded at 95% CL.

Regions of the non-universal G(221) parameter space excluded at 95% CL.

Number of expected $W^{\prime}_{\rm SSM}$, $W^{\prime}_{\rm NU}$, Standard Model background and observed events passing the optimal $m_{\rm T}$ threshold for each considered signal mass hypothesis. The expectations include the total statistical and systematic uncertainty added in quadrature. The yields and uncertainties are calculated before applying the statistical fitting procedure.

Number of expected $W^{\prime}_{\rm SSM}$, $W^{\prime}_{\rm NU}$, Standard Model background and observed events passing the optimal $m_{\rm T}$ threshold for each considered signal mass hypothesis. The expectations include the total statistical and systematic uncertainty added in quadrature. The yields and uncertainties are calculated before applying the statistical fitting procedure.

Number of expected $W^{\prime}_{\rm SSM}$, $W^{\prime}_{\rm NU}$, Standard Model background and observed events passing the optimal $m_{\rm T}$ threshold for each considered signal mass hypothesis. The expectations include the total statistical and systematic uncertainty added in quadrature. The yields and uncertainties are calculated before applying the statistical fitting procedure.

Acceptance for $W^{\prime}_{\rm SSM}$ as a function of the $W^{\prime}_{\rm SSM}$ mass, shown after successively applying selection at generator-level. The acceptance times efficiency is calculated with respect to all $W^{\prime}_{\rm SSM} \to \tau\nu$ events with a generated $\tau\nu$ mass above 120 GeV. The "selected tau" criteria include the requirement of a $\tau_{\rm had-vis}$ with $p_{\rm T}$ > 50 GeV and $|\eta|$ < 2.4. The $m_{\rm T}$ threshold for each $W^{\prime}_{\rm SSM}$ mass is defined in Table 5.

Acceptance for $W^{\prime}_{\rm SSM}$ as a function of the $W^{\prime}_{\rm SSM}$ mass, shown after successively applying selection at generator-level. The acceptance times efficiency is calculated with respect to all $W^{\prime}_{\rm SSM} \to \tau\nu$ events with a generated $\tau\nu$ mass above 120 GeV. The "selected tau" criteria include the requirement of a $\tau_{\rm had-vis}$ with $p_{\rm T}$ > 50 GeV and $|\eta|$ < 2.4. The $m_{\rm T}$ threshold for each $W^{\prime}_{\rm SSM}$ mass is defined in Table 5.

Acceptance for $W^{\prime}_{\rm SSM}$ as a function of the $W^{\prime}_{\rm SSM}$ mass, shown after successively applying selection at generator-level. The acceptance times efficiency is calculated with respect to all $W^{\prime}_{\rm SSM} \to \tau\nu$ events with a generated $\tau\nu$ mass above 120 GeV. The "selected tau" criteria include the requirement of a $\tau_{\rm had-vis}$ with $p_{\rm T}$ > 50 GeV and $|\eta|$ < 2.4. The $m_{\rm T}$ threshold for each $W^{\prime}_{\rm SSM}$ mass is defined in Table 5.

Acceptance times efficiency for $W^{\prime}_{\rm SSM}$ as a function of the $W^{\prime}_{\rm SSM}$ mass, shown after successively applying selection at reconstruction-level. The acceptance times efficiency is calculated with respect to all $W^{\prime}_{\rm SSM} \to \tau\nu$ events with a generated $\tau\nu$ mass above 120 GeV. "Preselection" includes all criteria prior to those shown. The $m_{\rm T}$ threshold for each $W^{\prime}_{\rm SSM}$ mass is defined in Table 5.

Acceptance times efficiency for $W^{\prime}_{\rm SSM}$ as a function of the $W^{\prime}_{\rm SSM}$ mass, shown after successively applying selection at reconstruction-level. The acceptance times efficiency is calculated with respect to all $W^{\prime}_{\rm SSM} \to \tau\nu$ events with a generated $\tau\nu$ mass above 120 GeV. "Preselection" includes all criteria prior to those shown. The $m_{\rm T}$ threshold for each $W^{\prime}_{\rm SSM}$ mass is defined in Table 5.

Acceptance times efficiency for $W^{\prime}_{\rm SSM}$ as a function of the $W^{\prime}_{\rm SSM}$ mass, shown after successively applying selection at reconstruction-level. The acceptance times efficiency is calculated with respect to all $W^{\prime}_{\rm SSM} \to \tau\nu$ events with a generated $\tau\nu$ mass above 120 GeV. "Preselection" includes all criteria prior to those shown. The $m_{\rm T}$ threshold for each $W^{\prime}_{\rm SSM}$ mass is defined in Table 5.

Reconstruction efficiency as a function of $m_{\rm T}$ (see HepData abstract for parameterization), defined as the ratio of the number of $\tau\nu$ events remaining after applying the full selection at reconstruction-level to those remaining after applying the fiducial selection at generator-level. The efficiency is largely model independent, with an uncertainty of ~10% due to model choice.

Reconstruction efficiency as a function of $m_{\rm T}$ (see HepData abstract for parameterization), defined as the ratio of the number of $\tau\nu$ events remaining after applying the full selection at reconstruction-level to those remaining after applying the fiducial selection at generator-level. The efficiency is largely model independent, with an uncertainty of ~10% due to model choice.

Reconstruction efficiency as a function of $m_{\rm T}$ (see HepData abstract for parameterization), defined as the ratio of the number of $\tau\nu$ events remaining after applying the full selection at reconstruction-level to those remaining after applying the fiducial selection at generator-level. The efficiency is largely model independent, with an uncertainty of ~10% due to model choice.

The three isolated photons cross section with systematic and statistical uncertainties as a function of DPhi(Photon1,Photon2).

The three isolated photons cross section with systematic and statistical uncertainties as a function of DPhi(Photon1,Photon3).

The three isolated photons cross section with systematic and statistical uncertainties as a function of DPhi(Photon2,Photon3).

The three isolated photons cross section with systematic and statistical uncertainties as a function of |DEta(Photon1,Photon2)|.

The three isolated photons cross section with systematic and statistical uncertainties as a function of |DEta(Photon1,Photon3)|.

The three isolated photons cross section with systematic and statistical uncertainties as a function of |DEta(Photon2,Photon3)|.

The three isolated photons cross section with systematic and statistical uncertainties as a function of M(Photon1,Photon2).

The three isolated photons cross section with systematic and statistical uncertainties as a function of M(Photon1,Photon3).

The three isolated photons cross section with systematic and statistical uncertainties as a function of M(Photon2,Photon3).

The three isolated photons cross section with systematic and statistical uncertainties as a function of M(Photon1,Photon2,Photon3).